This paper presents a corpus of tweets in Spanish language which were manually tagged for marketing purposes. The used tags describe three aspects of the text of each Twitter post. First, the emotions a brand caused to the author from among a taxonomy of emotions designed by marketing experts. Also, whether it mentioned any element of the marketing mix (including various relevant marketing concepts such as price or promotion). Finally, the position of the author of the tweet with respect to the acquisition process (or purchase funnel). Each Twitter post is related to only one brand, which is also indicated in the corpus. The corpus presented in this article is published in a machine-readable format as a collection of RDF documents with links to additional external information. The paper also includes details on the used vocabulary and the tagging criteria, as well as a description of the annotation process followed to tag the tweets.